AWS Machine Learning Blog

DECEMBER 7, 2023

In this post, we describe the end-to-end workforce management system that begins with location-specific demand forecast, followed by courier workforce planning and shift assignment using Amazon Forecast and AWS Step Functions. AWS Step Functions automatically initiate and monitor these workflows by simplifying error handling.

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Flipboard

DECEMBER 11, 2024

Many of these applications are complex to build because they require collaboration across teams and the integration of data, tools, and services. Data engineers use data warehouses, data lakes, and analytics tools to load, transform, clean, and aggregate data. Choose Create VPC.

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AWS Machine Learning Blog

OCTOBER 20, 2023

Customers of every size and industry are innovating on AWS by infusing machine learning (ML) into their products and services. However, implementing security, data privacy, and governance controls are still key challenges faced by customers when implementing ML workloads at scale.

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Precisely

MARCH 9, 2023

Data warehouse vs. data lake, each has their own unique advantages and disadvantages; it’s helpful to understand their similarities and differences. In this article, we’ll focus on a data lake vs. data warehouse. It is often used as a foundation for enterprise data lakes.

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Smart Data Collective

AUGUST 9, 2019

Big data in the gaming industry has played a phenomenal role in the field. We have previously talked about the benefits of using big data by gaming providers that offer cash games, such as slots. However, more mainstream games use big data as well. Big Data is the Lynchpin of the Fortnite Gaming Experience.

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AWS Machine Learning Blog

AUGUST 21, 2023

You can streamline the process of feature engineering and data preparation with SageMaker Data Wrangler and finish each stage of the data preparation workflow (including data selection, purification, exploration, visualization, and processing at scale) within a single visual interface.

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Women in Big Data

NOVEMBER 27, 2024

How to Choose a Data Warehouse for Your Big Data Choosing a data warehouse for big data storage necessitates a thorough assessment of your unique requirements. Begin by determining your data volume, variety, and the performance expectations for querying and reporting.

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Smart Data Collective

FEBRUARY 23, 2022

Traditional relational databases provide certain benefits, but they are not suitable to handle big and various data. That is when data lake products started gaining popularity, and since then, more companies introduced lake solutions as part of their data infrastructure. AWS Athena and S3.

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AWS Machine Learning Blog

AUGUST 8, 2024

As one of the largest AWS customers, Twilio engages with data, artificial intelligence (AI), and machine learning (ML) services to run their daily workloads. Data is the foundational layer for all generative AI and ML applications. The following diagram illustrates the solution architecture.

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Women in Big Data

OCTOBER 9, 2024

With the explosive growth of big data over the past decade and the daily surge in data volumes, it’s essential to have a resilient system to manage the vast influx of information without failures. The success of any data initiative hinges on the robustness and flexibility of its big data pipeline.

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Flipboard

NOVEMBER 27, 2024

Enterprises are facing challenges in accessing their data assets scattered across various sources because of increasing complexities in managing vast amount of data. Traditional search methods often fail to provide comprehensive and contextual results, particularly for unstructured data or complex queries.

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Flipboard

NOVEMBER 17, 2023

Specify the AWS Lambda function that will interact with MongoDB Atlas and the LLM to provide responses. As always, AWS welcomes feedback. About the authors Igor Alekseev is a Senior Partner Solution Architect at AWS in Data and Analytics domain. Choose Build and after the build is successful, choose Test.

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AWS Machine Learning Blog

MARCH 30, 2023

Therefore, it’s no surprise that determining the proficiency of goalkeepers in preventing the ball from entering the net is considered one of the most difficult tasks in football data analysis. Bundesliga and AWS have collaborated to perform an in-depth examination to study the quantification of achievements of Bundesliga’s keepers.

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AWS Machine Learning Blog

AUGUST 21, 2024

Amazon DataZone is a data management service that makes it quick and convenient to catalog, discover, share, and govern data stored in AWS, on-premises, and third-party sources. An Amazon DataZone domain and an associated Amazon DataZone project configured in your AWS account.

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ODSC - Open Data Science

JUNE 7, 2023

To make your data management processes easier, here’s a primer on data lakes, and our picks for a few data lake vendors worth considering. What is a data lake? First, a data lake is a centralized repository that allows users or an organization to store and analyze large volumes of data.

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AWS Machine Learning Blog

AUGUST 13, 2024

Amazon Bedrock offers a serverless experience, so you can get started quickly, privately customize FMs with your own data, and quickly integrate and deploy them into your applications using the AWS tools without having to manage the infrastructure. The Lambda function invokes an AWS Glue job and monitors for completion.

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Flipboard

NOVEMBER 24, 2023

In this post, we will talk about how BMW Group, in collaboration with AWS Professional Services, built its Jupyter Managed (JuMa) service to address these challenges. For example, teams using these platforms missed an easy migration of their AI/ML prototypes to the industrialization of the solution running on AWS.

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AWS Machine Learning Blog

FEBRUARY 13, 2024

SageMaker Feature Store now makes it effortless to share, discover, and access feature groups across AWS accounts. With this launch, account owners can grant access to select feature groups by other accounts using AWS Resource Access Manager (AWS RAM). Review the access policy to understand permissions granted.

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AWS Machine Learning Blog

FEBRUARY 28, 2024

Third, despite the larger adoption of centralized analytics solutions like data lakes and warehouses, complexity rises with different table names and other metadata that is required to create the SQL for the desired sources. Our solution aims to address those challenges using Amazon Bedrock and AWS Analytics Services.

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Pickl AI

SEPTEMBER 18, 2024

Summary: Netflix’s sophisticated Big Data infrastructure powers its content recommendation engine, personalization, and data-driven decision-making. As a pioneer in the streaming industry, Netflix utilises advanced data analytics to enhance user experience, optimise operations, and drive strategic decisions.

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Dataconomy

SEPTEMBER 4, 2023

Big data analytics: Big data analytics is designed to handle massive volumes of data from various sources, including structured and unstructured data. Big data analytics is essential for organizations dealing with large-scale data, such as social media platforms, e-commerce giants, and scientific research.

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Data Science 101

NOVEMBER 7, 2019

Azure Synapse Analytics can be seen as a merge of Azure SQL Data Warehouse and Azure Data Lake. Synapse allows one to use SQL to query petabytes of data, both relational and non-relational, with amazing speed. Those are the big data science announcements of the week. Azure Synapse.

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AWS Machine Learning Blog

JANUARY 4, 2024

In this pattern, we use Retrieval Augmented Generation using vector embeddings stores, like Amazon Titan Embeddings or Cohere Embed , on Amazon Bedrock from a central data catalog, like AWS Glue Data Catalog , of databases within an organization. In entered the Big Data space in 2013 and continues to explore that area.

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AWS Machine Learning Blog

DECEMBER 18, 2023

sales-train-data is used to store data extracted from MongoDB Atlas, while sales-forecast-output contains predictions from Canvas. In his role Igor is working with strategic partners helping them build complex, AWS-optimized architectures. Note we have two folders.

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AWS Machine Learning Blog

NOVEMBER 9, 2023

Central model registry – Amazon SageMaker Model Registry is set up in a separate AWS account to track model versions generated across the dev and prod environments. with administrative privileges installed on AWS Terraform version 1.5.5 After the key is provisioned, it should be visible on the AWS KMS console.

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AWS Machine Learning Blog

NOVEMBER 12, 2024

You may check out additional reference notebooks on aws-samples for how to use Meta’s Llama models hosted on Amazon Bedrock. You can implement these steps either from the AWS Management Console or using the latest version of the AWS Command Line Interface (AWS CLI). Solutions Architect at AWS. Varun Mehta is a Sr.

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ODSC - Open Data Science

FEBRUARY 2, 2023

Big Data As datasets become larger and more complex, knowing how to work with them will be key. Big data isn’t an abstract concept anymore, as so much data comes from social media, healthcare data, and customer records, so knowing how to parse all of that is needed.

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AWS Machine Learning Blog

APRIL 18, 2023

It includes sensor devices to capture vibration and temperature data, a gateway device to securely transfer data to the AWS Cloud, the Amazon Monitron service that analyzes the data for anomalies with ML, and a companion mobile app to track potential failures in your machinery.

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Smart Data Collective

MARCH 21, 2022

Data Mesh which is the latest addition to the stack is saving data teams from the hassle of producing qualitative data for all business types. Most recently, JP Morgan built a ‘Mesh’ on AWS and locked its scalability fortune on a decentralized architecture. Data Management before the ‘Mesh’.

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AWS Machine Learning Blog

AUGUST 2, 2023

We demonstrate CDE using simple examples and provide a step-by-step guide for you to experience CDE in an Amazon Kendra index in your own AWS account. Marketing firms store vast amounts of digital data that needs to be centralized, easily searchable, and scalable enabled by data catalogs.

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Smart Data Collective

AUGUST 5, 2021

In this blog, we will cover an overview of Delta Lakes , its advantages, and how the above challenges can be overcome by moving to Delta Lake and migrating to Spark 3.0 What is Delta Lake? Using Delta Lake and Spark 3.0, from Spark 2.4. . End Result.

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AWS Machine Learning Blog

MAY 15, 2023

We outline how we built an automated demand forecasting pipeline using Forecast and orchestrated by AWS Step Functions to predict daily demand for SKUs. On an ongoing basis, we calculate mean absolute percentage error (MAPE) ratios with product-based data, and optimize model and feature ingestion processes.

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ODSC - Open Data Science

JULY 27, 2023

Choosing a Data Lake Format: What to Actually Look For The differences between many data lake products today might not matter as much as you think. When choosing a data lake, here’s something else to consider. When choosing a data lake, here’s something else to consider.

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Pickl AI

OCTOBER 10, 2024

Enhanced Data Quality : These tools ensure data consistency and accuracy, eliminating errors often occurring during manual transformation. Scalability : Whether handling small datasets or processing big data, transformation tools can easily scale to accommodate growing data volumes.

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Precisely

JANUARY 19, 2023

Organizations that can master the challenges of data integration, data quality, and context will be well positioned to identify opportunities and threats quickly, and then to take decisive action to gain competitive advantage. Mainframes have long been valued for those very same attributes.

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phData

NOVEMBER 8, 2024

Note : Cloud Data warehouses like Snowflake and Big Query already have a default time travel feature. However, this feature becomes an absolute must-have if you are operating your analytics on top of your data lake or lakehouse. It can also be integrated into major data platforms like Snowflake.

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ODSC - Open Data Science

APRIL 3, 2023

Data Wrangling: Data Quality, ETL, Databases, Big Data The modern data analyst is expected to be able to source and retrieve their own data for analysis. Competence in data quality, databases, and ETL (Extract, Transform, Load) are essential. Cloud Services: Google Cloud Platform, AWS, Azure.

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